Mediterranean Machine Learning Summer School
Split, Croatia
Split, Croatia
8-12 September 2025
The 2025 Mediterranean Machine Learning (M2L) summer school will be structured around 5 days of keynotes, lectures and practical sessions. The program will include social or cultural activities to foster networking. Participants will be encouraged to (optionally) present their work at poster sessions during the school and to interact with our sponsors and with each other during the coffee breaks throughout the week.
Lectures and laboratories will be taught by local and international AI experts. State-of-the-art content and code will be accessible to all participants.
See Past editions for typical school programs.
Location and dates:
The 2025 edition of the Mediterranean Machine Learning (M2L) summer school will take place in Croatia in September.
Audience:
The target audience consists primarily of advanced Master students, and Doctoral students, academics and practitioners from all around the world, with a focus on the Mediterranean area. The school will be advertised with a public call and participants will be selected on the basis of merit and to promote diversity. Preferred attendees have a technical background, and some prior understanding and practical experience of machine learning.
Topics:
Computer vision
Natural Language Processing
Generative and diffusion models
Reinforcement learning
Graph neural networks
Self-supervised learning
Applied deep learning
Neuroscience
Ethics in machine learning
....and many more!
Founding principles
Promote diversity and inclusion: AI is revolutionizing several fields, from computer vision to autonomous driving and robotics. Its potential to radically change our society calls for this technology to be mastered and shaped by everyone, with equal representation of genders, ethnicities, nationalities, religions and economic backgrounds.
Boost networking and knowledge transfer: M2L brings together early-stage researchers, practitioners and world-leading experts, providing access to high quality education, and strengthening the local and foreign machine learning ecosystem by fostering durable connections among researchers, as well as among practitioners and industry.
Support dialogue and collaboration: the school aims to promote an informed dialogue among companies, academia and institutions, encouraging them to take an active role in shaping, regulating and supporting the evolution of the artificial intelligence field, as well as to facilitate the exchange of ideas and the establishment of partnerships.
Testimonials